<abstract xmlns="http://www.w3.org/1999/xhtml">
        
        <p> Health care accessibility can be measured by the number of prospective patients who could reach a medical facility within a prescribed time limit. The representation of health care demand in estimating accessibility is an important consideration since different spatial aggregations of demand have different consequences with regard to accessibility estimates. This article examines the effects of aggregating population demand for primary health care, ranging from census tract to aggregated census block, on estimates of primary health care accessibility. Spatial representations of aggregated demand were incorporated into a location-allocation model in order to determine a measure of accessibility represented by the unmet demand for primary health care services. The model was implemented for the U.S. State of Idaho, based on the allocation of Idaho residents’ demand for primary health care to the state’s existing primary health care facilities. The results confirm a relationship between the level of demand aggregation and the level of potential accessibility. In case of a rural state such as Idaho the relationship is positive; higher levels of aggregation result in higher measures of accessibility.</p>
      </abstract>

Health care accessibility can be measured by the number of prospective patients who could reach a medical facility within a prescribed time limit. The representation of health care demand in estimating accessibility is an important consideration since different spatial aggregations of demand have different consequences with regard to accessibility estimates. This article examines the effects of aggregating population demand for primary health care, ranging from census tract to aggregated census block, on estimates of primary health care accessibility. Spatial representations of aggregated demand were incorporated into a location-allocation model in order to determine a measure of accessibility represented by the unmet demand for primary health care services. The model was implemented for the U.S. State of Idaho, based on the allocation of Idaho residents’ demand for primary health care to the state’s existing primary health care facilities. The results confirm a relationship between the level of demand aggregation and the level of potential accessibility. In case of a rural state such as Idaho the relationship is positive; higher levels of aggregation result in higher measures of accessibility.

Health Care Accessibility Modeling: Effects of Change in Spatial Representation of Demand for Primary Health Care Services

Department of Geography, San Diego State University, San Diego, CA, USA

Institute of Geoecology and Geoinformation, Adam Mickiewicz University in Poznań, Poland

Quaestiones Geographicae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Health care accessibility can be measured by the number of prospective patients who could reach a medical facility within a prescribed time limit. The...

Health Care Accessibility Modeling: Effects of Change in Spatial Representation of Demand for Primary Health Care Services

Online veröffentlicht: 19. Sept. 2014

Seitenbereich: 39 - 53

Eingereicht: 05. Mai 2013

DOI: https://doi.org/10.2478/quageo-2013-0028

Schlüsselwörter
health care accessibility, GIS, location-allocation, scale, spatial aggregation

© Faculty of Geographical and Geological Sciences, Adam Mickiewicz University

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Health Care Accessibility Modeling: Effects of Change in Spatial Representation of Demand for Primary Health Care Services

Online veröffentlicht: 19. Sept. 2014

Seitenbereich: 39 - 53

Eingereicht: 05. Mai 2013

DOI: https://doi.org/10.2478/quageo-2013-0028

Schlüsselwörterhealth care accessibility, GIS, location-allocation, scale, spatial aggregation

© Faculty of Geographical and Geological Sciences, Adam Mickiewicz University

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
health care accessibility, GIS, location-allocation, scale, spatial aggregation